An intelligent proactive defense against the client‐side DNS cache poisoning attack via self‐checking deep reinforcement learning
Sign Up to like & getrecommendations! Published in 2022 at "International Journal of Intelligent Systems"
DOI: 10.1002/int.22934
Abstract: A new class of poisoning attacks has recently emerged targeting the client‐side Domain Name System (DNS) cache. It allows users to visit fake websites unconsciously, thereby revealing their information, such as passwords. However, the current… read more here.
Keywords: proactive defense; deep reinforcement; client side; defense ... See more keywords
Privacy-preserving remote deep-learning-based inference under constrained client-side environment
Sign Up to like & getrecommendations! Published in 2021 at "Journal of Ambient Intelligence and Humanized Computing"
DOI: 10.1007/s12652-021-03312-8
Abstract: Remote deep learning paradigm raises important privacy concerns related to clients sensitive data and deep learning models. However, dealing with such concerns may come at the expense of more client-side overhead, which does not fit… read more here.
Keywords: privacy; constrained client; client side; deep learning ... See more keywords
Client-Side Optimization Strategies for Communication-Efficient Federated Learning
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Communications Magazine"
DOI: 10.1109/mcom.005.210108
Abstract: Federated learning (FL) is a swiftly evolving field within machine learning for collaboratively training models at the network edge in a privacy-preserving fashion, without training data leaving the devices where it was generated. The privacy-preserving… read more here.
Keywords: federated learning; side optimization; client side;
Shielding Collaborative Learning: Mitigating Poisoning Attacks Through Client-Side Detection
Sign Up to like & getrecommendations! Published in 2021 at "IEEE Transactions on Dependable and Secure Computing"
DOI: 10.1109/tdsc.2020.2986205
Abstract: Collaborative learning allows multiple clients to train a joint model without sharing their data with each other. Each client performs training locally and then submits the model updates to a central server for aggregation. Since… read more here.
Keywords: detection; client side; poisoning attacks; collaborative learning ... See more keywords
A Study of Causes and Consequences of Client-Side JavaScript Bugs
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DOI: 10.1109/tse.2016.2586066
Abstract: Client-side JavaScript is widely used in web applications to improve user-interactivity and minimize client-server communications. Unfortunately, JavaScript is known to be error-prone. While prior studies have demonstrated the prevalence of JavaScript faults, no attempts have… read more here.
Keywords: client side; javascript faults; causes consequences; side javascript ... See more keywords
Client-Side Application of Deep Learning Models Through Teleradiology.
Sign Up to like & getrecommendations! Published in 2023 at "Studies in health technology and informatics"
DOI: 10.3233/shti230325
Abstract: Deep learning models for radiology are typically deployed either through cloud-based platforms, through on-premises infrastructures, or though heavyweight viewers. This tends to restrict the audience of deep learning models to radiologists working in state-of-the-art hospitals,… read more here.
Keywords: client side; learning models; application deep; deep learning ... See more keywords
Real-Time Flood Mapping on Client-Side Web Systems Using HAND Model
Sign Up to like & getrecommendations! Published in 2021 at "Hydrology"
DOI: 10.3390/hydrology8020065
Abstract: The height above nearest drainage (HAND) model is frequently used to calculate properties of the soil as well as predict flood inundation extents. HAND is extremely useful due to its lack of reliance on prior… read more here.
Keywords: flood mapping; client side; hand; hand model ... See more keywords